In accordance with conventional image capturing, a device such as a camera can include an image sensor. Each of the multiple sensor elements in the image sensor detects a portion of light associated with an image being captured. Depending on an amount of detected light, a respective sensor element in the image sensor produces an output value indicative of the detected intensity of optical energy. Collectively, output values from each of the individual sensor elements in the array define attributes of an image captured by the camera. Based on output values from the sensor elements in the image sensor, it is possible to store, reconstruct, and display a rendition of a captured image.
It is not uncommon that an image sensor includes one or more defective sensor elements that do not produce accurate output values. This is especially true for lower cost image sensors. If a sensor element is defective, the respective output values of the defective sensor element can be excluded from a final version of an image to preserve the image's accuracy.
In some cases, sensor elements in an image sensor may not completely fail. For example, a defective sensor element may be able to partially detect optical energy and produce an output value that varies depending on detected optical intensity. However, the output values produced by the image sensor may be very inaccurate and therefore unusable in a final version of an image.
One way to manage defective sensor elements is to treat the defective sensor elements as being dead and replacing an output value of the defective sensor element with a value derived from one or more outputs of nearby sensor elements. If the algorithm to detect a bad sensor element is done incorrectly, for example, by generating replacement values when the sensor elements are actually not defective, results in degrading the quality of a respective image.
In general, methods for handling defective sensor elements can be divided into two categories: static and dynamic. Static methods can include use of a table to keep track of the defective sensor elements in an image sensor. Dynamic methods on the other hand attempt to determine defective sensor elements by looking for incongruous pixel data in each picture.
It may be desirable to use both methods (dynamic and static) at the same time, and possibly even use the dynamic defective pixel detection, to modify the list of static defective sensor elements.
One type of image sensor includes a patterned color filter such as a Bayer filter. Bayer filters are commonly used in single-chip digital image sensors installed in digital cameras, camcorders, and scanners to capture color images. A Bayer filter pattern can include 50% green pixels, 25% red pixels, and 25% blue pixels. A Bayer filter is sometimes called RGBG, GRGB, or RGGB.
In accordance with the Bayer pattern and filtering, each sensor element in a respective image sensor includes either a red, green, or blue filter to filter incoming light that strikes a corresponding sensor element. More specifically, for a sensor element including a respective red filter, the sensor element detects an intensity of red light that passes through the respective red filter. For a sensor element including a respective blue filter, the sensor element detects an intensity of blue light that passes through the respective blue filter. For a sensor element including a respective green filter, the sensor element detects an intensity of green that passes through the respective green filter.
Via the intensity of different colors detected by the sensor elements in different regions of the image sensor, it is possible to reproduce a respective image on a display screen.